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Summary
Read YouTube data — videos, channels, playlists, search, comments — and (with OAuth) manage your own uploads. 9 tools, API key + optional OAuth Bearer.
Try asking
Example prompts for YouTube Data API
Click any prompt to copy it. Paste into Claude, ChatGPT, Cursor, Gemini, Copilot or OpenClaw to run it against this connector.
Claude is AI and can make mistakes. Please double-check responses.
💡 No install? Use cloud.anythingmcp.com directly. Sign in, click Connectors → YouTube Data API, paste your credentials, mint an MCP API key — done. No Docker, no
git clone, no local server.
YouTube Data API + Gemini
Read YouTube data — videos, channels, playlists, search, comments — and (with OAuth) manage your own uploads. 9 tools, API key + optional OAuth Bearer.
Prerequisites
See the full setup instructions baked into the connector (visible in the in-app store when you select the connector). The required environment variables for this connector are:
YOUTUBE_API_KEY
Step 1 — Get credentials
Setup:
- Create / pick a Google Cloud project at https://console.cloud.google.com.
- APIs & Services → Library → enable YouTube Data API v3.
- Credentials → Create credentials → API key. (For write operations, also do OAuth2 client + get a Bearer token with
youtube.upload/youtubescopes — out of scope here.) - Set
YOUTUBE_API_KEYto the API key.
Authentication: query-string ?key=.... Read operations don't need OAuth.
…(continued in the in-app connector instructions)
Step 2 — Install the adapter
curl -fsSL https://raw.githubusercontent.com/HelpCode-ai/anythingmcp/main/docker-compose.quickstart.yml -o docker-compose.yml
printf 'JWT_SECRET=%s\nENCRYPTION_KEY=%s\n' "$(openssl rand -hex 32)" "$(openssl rand -hex 32)" > .env
docker compose up -d
Step 3 — Add the connector in Gemini
Your server URL: in AnythingMCP, open MCP Servers → the server this connector is on, and copy its URL (
https://cloud.anythingmcp.com/mcp/…). Use it wherever this guide showsYOUR_SERVER_ID.
Gemini CLI reads MCP servers from ~/.gemini/settings.json (or %APPDATA%\gemini\settings.json on Windows). Add:
{
"mcpServers": {
"anythingmcp": {
"httpUrl": "https://cloud.anythingmcp.com/mcp/YOUR_SERVER_ID",
"headers": { "X-API-Key": "YOUR_MCP_API_KEY" }
}
}
}
- Get your MCP API key from AnythingMCP → MCP Servers → your server → API keys.
- Save the file and restart
gemini. - Run
/mcpinside the Gemini CLI —YouTube Data APIshould be listed as available. - Vertex AI Studio: pass
https://cloud.anythingmcp.com/mcp/YOUR_SERVER_IDto thetoolsarray of your request with the sameX-API-Keyheader.
Available tools
| Tool | What it does |
|---|---|
youtube_search | Search videos / channels / playlists |
youtube_get_videos | Fetch video details by ID(s) |
youtube_get_videos_chart | Get videos from a chart (currently only 'mostPopular') |
youtube_get_channels | Fetch channel details by ID, handle (@username), forUsername (legacy), or 'mine' (requires OAuth) |
youtube_list_playlists | List playlists, filtered by channelId or 'mine' (OAuth) |
youtube_list_playlist_items | List items in a playlist (videos in playlist) |
youtube_list_video_comments | List top-level comments on a video |
youtube_list_categories | List video categories for a region |
youtube_get_captions | List caption tracks available for a video |
FAQ
Does Gemini 1.5 Pro or 2.x support MCP? Yes — Gemini CLI ≥ 0.4 and Vertex AI tools API both accept MCP httpUrl connectors with custom headers.
Next steps
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